IRGL-RRI: interpretable graph representation learning for plant RNA-RNA interaction discovery. [PDF]
Liao Q +6 more
europepmc +1 more source
Bacterial α‐diversity decreases, but stochasticity and community stability increase across the 15 m‐depth vertical profiles and along the degraded gradient within the active layer. The abundance and interaction of core taxa mainly control community stability in the active and permafrost layers, respectively.
Shengyun Chen +13 more
wiley +1 more source
MultiGATE: integrative analysis and regulatory inference in spatial multi-omics data via graph representation learning. [PDF]
Miao J +9 more
europepmc +1 more source
All-optical graph representation learning using integrated diffractive photonic computing units. [PDF]
Yan T +5 more
europepmc +1 more source
By integrating single‐nuclei and spatial transcriptomics, this study presents a stereoscopic landscape of maize leaf to Puccinia polysora infection. Epidermal and mesophyll cells initiate primary defenses via RLPs/RLKs and jasmonic acid signaling. Cell‐cell communication analyses further reveal the underlying the dynamics of the underlying immune ...
Qiongqiong Wang +16 more
wiley +1 more source
AGRL-DSE: Adaptive Graph Representation Learning on a Heterogeneous Graph for Drug Side Effect Prediction. [PDF]
Tan H +6 more
europepmc +1 more source
Multi-Scale Graph Representation Learning for Autism Identification With Functional MRI. [PDF]
Chu Y, Wang G, Cao L, Qiao L, Liu M.
europepmc +1 more source
Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee +4 more
wiley +1 more source
Decoding potential lncRNA and disease associations through graph representation learning and gradient boosting with histogram. [PDF]
Tang L, Liu L, Jiang Y, Yuan Y.
europepmc +1 more source
Time-varying graph representation learning via higher-order skip-gram with negative sampling. [PDF]
Piaggesi S, Panisson A.
europepmc +1 more source

